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Abstract A methodolgy for assessment of the predictive ability of regression models is presented. Attention is given to models obtained via subset selection procedures, which are extremely difficult to evaluate by standard techniques. Cross-validatory assessments of predictive ability are obtained and their use illustrated in examples.
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Journal of the American Statistical Association
University of Minnesota
Los Alamos National Laboratory
University of Minnesota System
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